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The goal of this study is to test whether autonomous vehicles are perceived as social entities and subject to the same social and or moral norms of cooperation as human traffic participants are. Specifically, we test whether individuals’ prosocial behavioral intentions in different traffic situations change depending on their interaction with autonomous or human-driven vehicles, and whether this might be caused by variations in the activation of social norms for the specific vehicle type.

This experiment improves the measurement of political solidarities, i.e. the individual willingness to support public redistribution in favour of other people. In order to explore behavioural instruments that can be implemented in online surveys, we focus on an extended version of the solidarity game (Ockenfels/Selten 1998) that we adapt to the online environment and contextualise for our purposes with different levels of information. The original instrument was designed to measure implicit reciprocity and the amount of empathy that makes deciders to imagine themselves being in the losers’ shoes. Why can some social groups maintain high levels of solidarity while others fail? Regarding the political domain, transparency about other individual’s behavour is often presumed to positively affect participation and social cohesion. However, the role of transparency on the behavioural salience of social norms is less clear. We ask in this study: How does transparency about solidarity affect the willingness to act in solidarity? Solidarity is voluntary compensation to group members if they experience an income loss due to a random adverse event (e.g., natural disaster). A credible commitment to solidarity is crucial to achieving and maintaining solidarity within social groups. This study tests the causal effect of transparency about the social norm of solidarity on actual behavior. This study tests the effect of transparency about solidarity on solidarity behavior in social groups. We know that subjects’ assumptions about the prevalence of a specific social norm (e.g., honesty, cooperativeness) in groups strongly affect their choice to adhere to the norm and act accordingly. In other words, adherence to a social norm is conditional on others’ adherence. Previous research, for example, shows that honest people start to cheat more once they know about the number of “cheaters” in their group. Likewise, in public goods games, the willingness to contribute among those who contribute in the first round declines once they learn about the number of free riders in their group.

This experiment is to improve the measurement of political solidarities, i.e. the individual willingness to support public redistribution in favour of other people. In order to explore behavioural instruments that can be implemented in online surveys, we focus on an extended version of the solidarity game (Ockenfels/Selten 1998) that we adapt to the online environment and contextualise for our purposes with different levels of information. The original instrument was designed to measure implicit reciprocity and the amount of empathy that makes deciders to imagine themselves being in the losers’ shoes.

This study is part of the POLITSOLID project and tests the behavioural consequences of solidarity in contexts where the presence of solidarity in a social group is known or unknown. Solidarity behaviour is voluntary compensation to group members when they experience an income loss due to a random adverse event (e.g., natural disaster). We know that subjects’ assumptions about the prevalence of a specific social norm (e.g., honesty, cooperativeness) in groups strongly affect their choice to adhere to the norm and act accordingly. In other words, adherence to a social norm is conditional on others’ adherence to that norm. To measure solidarity behaviour, we utilize an extended version of the solidarity game by Ockenfels & Selten (1998) in which we manipulate respondents’ information about the solidarity behaviour of others. We correlate the measured, incentivised behaviour with party preferences in order to assess to what extent voters of parties that demand more public redistribution also show solidarity behaviour that is congruent with their party preference. Both party preferences and solidarity behaviour are driven by an underlying political ideology.

In this project, we investigate how responsibility for the risk to become needy affects solidarity within groups. The study is inspired by the recent COVID-19 pandemic and the decision to get vaccinated. Vaccinations reduce the personal probability of becoming needy as well as the risk of other members of the society to become needy. Our study disentangles these effects focusing on two independent variables; 1) the individual responsibility for becoming needy, and 2) the externalities of individual decisions of the probability of other group members to become needy. In an incentivized online experiment, we investigate how responsibility to become needy and externalities affect solidarity among group members.

This study explores the relationship between social and socio-demographic characteristics and solidarity behaviour. Solidarity behaviour is the voluntary compensation to group members if they experience an income loss due to a random adverse event (e.g., natural disaster). We know that subjects’ assumptions about the prevalence of a specific social norm (e.g., honesty, cooperativeness) in groups strongly affect their choice to adhere to the norm and act accordingly. In other words, adherence to a social norm is conditional on others’ adherence. To measure solidarity behaviour, we utilize an extended version of the solidarity game by Ockenfels & Selten (1998) in which we manipulate respondents’ information about the solidarity of others. The behavioural solidarity measure is analysed together with respondents’ social and socio-demographic characteristics. We collect data in an online setting from a much more diverse sample of adults in Germany and Austria and can thus test whether social characteristics, such as age, income and gender, can predict solidarity behaviour.

Preferences for the use and regulation of algorithms in the context of self-driving cars and algorithmic decision-making